Automation & AI · Checklist
An AI-readiness checklist for SMEs
AI readiness is operational readiness.
Last reviewed: July 17, 2026
3 min · Read
Summary
Before adding a model, define the task, data boundary, acceptable error, backup procedure and record of what happened. This creates clear responsibilities and testable limits.
Choose a support task
Good initial tasks include summarizing a known document set, classifying requests, drafting from approved context, extracting fields or preparing a quality review.
Choose work where the output can be checked and an incorrect result cannot silently move the process forward.
Set the boundary
List allowed references, prohibited data, retention expectations, roles and the decision the output may influence.
Define whether the output is a suggestion, draft, score or instruction to send work to the right person. Make that status visible.
Evaluate and operate
Create representative examples, expected outputs and failure cases. Review false positives and omissions, and keep a backup procedure independent of the model.
Assign an owner for prompt, reference and policy changes.
Practical checklist
- Is the task narrow?
- Is the reference approved?
- Is sensitive data minimized?
- Is output status visible?
- Can the output be checked?
- Are failures testable?
- Is there a backup procedure?
- Who owns changes?
Related solutions
- AI and operational support
- Operations and process automation
Next step
See how this decision applies to your business.
The diagnosis connects the framework to your real process, data and constraints.